Let's Talk about the Talk: Exploring the Experience of Discussing Student Performance at the Mid- and Final Points of the Clinical Internship
Bibliographic record
Abstract
Purpose: The purpose of this study was to explore the experiences of physiotherapy students and clinical instructors (CIs) when discussing student clinical performance at the mid- and final points of clinical internships. The objectives were to identify why performance assessment discussions are valuable, explore the role of each participant throughout the discussion, identify the challenges associated with these discussions, and explore the effect of the standardized assessment tool on the discussion. Methods: This study used a qualitative descriptive design, consisting of student and CI focus groups in the Greater Toronto Area from January to June 2016. Results: All participants (N=29) recognized the importance of having face-to-face performance assessment discussions in a quiet and private space. Students and CIs agreed that the Canadian Physiotherapy Assessment of Clinical Performance helped to structure and focus the discussions. Valuable discussions occurred when students were open minded and self-reflected on their performance and when CIs were honest and used their expertise to guide learning. Other key features included mutual preparedness, two-way feedback that was constructive and tangible, and a goal-setting process. Students described the emotional component of these discussions as being challenging, and CIs found it difficult when a student took a more passive role in the discussion. Conclusions: Our findings indicate that valuable discussions can provide meaningful feedback, strengthen the student–CI relationship, and engage the learner in an ongoing and cumulative learning process that contributes to professional development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".